Premium
System identification using discrete orthogonal functions
Author(s) -
Fahmy M. F.,
Haweei T. I.,
Elraheem G. J. M.,
Gharieb R. R.
Publication year - 1993
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.4490210402
Subject(s) - orthogonality , infinite impulse response , identification (biology) , control theory (sociology) , convergence (economics) , adaptive filter , transfer function , computer science , independence (probability theory) , system identification , filter (signal processing) , property (philosophy) , set (abstract data type) , orthogonal functions , mathematics , algorithm , digital filter , engineering , control (management) , philosophy , database , artificial intelligence , economic growth , mathematical analysis , biology , geometry , epistemology , computer vision , programming language , measure (data warehouse) , statistics , botany , electrical engineering , economics
In this paper a novel method is described for the design of adaptive IIR filters used in system identification. the adaptive filter is implemented as a parallel connection of subsections whose transfer functions constitute a set of discrete orthogonal systems. the adaptation algorithm used, which is of the Gauss‐Newton type, adjusts the parameters of these discrete orthogonal systems in order to match the desired output data of the unknown plant in a least squares sense. Owing to the orthogonality property, which ensures complete independence of subsequent sections, convergence is very rapid. Closed‐form expressions for the gradient signals required to update the filter are given. Illustrative examples have shown that this method always results in much improved adaptation properties compared with the already existing approaches.